**A) Context & Measures (*Sections 8.1 - 8.2*)** - **Data**: 01) **Raw data** - *CJ_00c raw CJ data Visarts.RData* contains raw data of orginality assessment - *Overview of 'CJ_00c raw CJ data Visarts.RData'.pdf* describes the variables in the raw data file 02) **Data for analysis** - *01A VisartsAnalysis12.RData* contains data used for analysis - *Overview of '01A VisartsAnalysis12.RData'.pdf* describes the variables in the data for analysis - **Scripts** 01) **Preparation** includes the scripts that were used to - perform a general check (*01P Visarts_gen_check.R*) - operationalize task exposure (*02P Visarts_task_exp.R*) - estimate the relative quality of the objects (*03P Visarts_est_qual.R*) - operationalize the three pair characteristics (*04P Visarts_info_char.R*) - operationalize task difficulty (*05P Visarts_task_dependent.R*) 02) **Outliers, distribution and subsetting** includes the scripts that were used to - check on outliers with regard to judgement time (*01ODS Visarts_outliers.R*) - identify the distribution of judgement time (*02ODS Visarts_JT_distribution.R*) - prepare the data for analysis (*03ODS Visarts_data_prep.R*) 03) **Context & measures** includes the scripts that were used to - calculate the descriptive statistics reported in sections 8.1 and 8.2 (*01CM Visarts_context_measures.R*) - create Figure 8.1 on the correlation during the assessment (*02CM Visarts_plot_cor_dependents.R*) ---------- **B) Analyses** - **Judgement time** includes the scripts that were used to - model hypothesis 1 and select the best model(s) (*01A Visarts_JT_H1.R*) - model hypothesis 2 and select the best model(s) (*02A Visarts_JT_H2.R*) - model hypothesis 3 and select the best model(s) (*03A Visarts_JT_H3.R*) - model hypothesis 4 and select the best model(s) (*04A Visarts_JT_H4.R*) - model combinations of hypotheses 2-4 and select the best model(s) (*05A Visarts_JT_H234.R*) - **Perceived task difficulty** includes the scripts that were used to - model hypothesis 1 and select the best model(s) (*01A Visarts_PTD_H1.R*) - model hypothesis 2 and select the best model(s) (*02A Visarts_PTD_H2.R*) - model hypothesis 3 and select the best model(s) (*03A Visarts_PTD_H3.R*) - model hypothesis 4 and select the best model(s) (*04A Visarts_PTD_H4.R*) - model combinations of hypotheses 2-4 and select the best model(s) (*05A Visarts_PTD_H234.R*) - **Decision inaccuracy** includes the scripts that were used to - model hypothesis 1 and select the best model(s) (*01A Visarts_DI_H1.R*) - model hypothesis 2 and select the best model(s) (*02A Visarts_DI_H2.R*) - model hypothesis 3 and select the best model(s) (*03A Visarts_DI_H3.R*) - model hypothesis 4 and select the best model(s) (*04A Visarts_DI_H4.R*) - model combinations of hypotheses 2-4 and select the best model(s) (script *05A Visarts_DI_H234.R*) ---------- **C) Results on *AIC* model selection (*Section 8.4*)** includes the scripts that were used to - summarize the results on *AIC* model selection (*01R Visarts_summary_AIC.R*) - perform checks on multicollinearity and absolute fit of the selected models (reported in Tables 8.15 to 8.17) (*02R Dots_check_models.R*) ---------- **D) Evidence about hypotheses (*Sections 8.5 - 8.7*)** includes the scripts that were used to - create Tables 8.15 to 8.17 that summarize the parameters of the selected model(s) (*01E Dots_summary_models.R*) - create Figures 8.2 and 8.3 on the relation of task exposure with the dependent variables (*02E Visarts_H1_plots.R*) - create Figures 8.4, 8.5, 8.6, 8.7 and 8.8 on relation of pair characteristics with the dependent variables (*02E Visarts_H234_plots.R*)